MUMBAI, India, Nov. 2 -- Intellectual Property India has published a patent application (202641127374 A) filed by Karpagam Academy Of Higher Education; Karpagam Institute Of Technology; Muruganandam S; and Rohan R on October 26, 2026, for Medical Information Enuiry Chatbot Using Artificial.
Inventors include Muruganandam S; and Rohan R.
The application for the patent was published on October 30, 2026, under issue no. 44/2026.
Abstract: The increasing demand for accessible and cost-effective healthcare services has highlighted the limitations of traditional medical consultation systems, particularly in terms of time constraints, availability of medical professionals, and rising healthcare expenditures. Many individuals delay seeking medical advice due to these barriers, resulting in inadequate early-stage health assessment and reduced awareness of potential medical conditions. To address these challenges, this work presents an artificial intelligence–based medical information enquiry chatbot designed to provide preliminary healthcare guidance through intelligent conversational interaction. The proposed system employs machine learning algorithms and natural language processing techniques to interpret user-provided health-related inputs, including symptoms described in free-form text or voice. By analyzing these inputs, the chatbot identifies relevant symptom patterns and maps them to trained medical datasets to generate informative, context-aware responses. Unlike traditional rule-based systems, the learning-driven approach enables the chatbot to adapt and improve its performance as the training data evolves, thereby enhancing accuracy and reliability in medical information delivery. The chatbot functions as a virtual healthcare assistant capable of answering queries related to common illnesses, symptoms, preventive measures, and general health awareness. The conversational interface is designed to simulate human-like interaction, enabling users to engage naturally without requiring predefined input formats. This improves usability and ensures wider acceptance among users with varying technical literacy levels. Additionally, the integration of text-to-speech functionality allows responses to be converted into audio output, improving accessibility for visually impaired users and individuals with reading difficulties. The system architecture supports real-time operation and scalable deployment across multiple platforms, including web-based applications, mobile devices, and remote healthcare systems. Continuous availability ensures that users can obtain medical information at any time without geographical limitations. The chatbot is positioned as a supportive and educational tool rather than a replacement for professional medical diagnosis, encouraging responsible usage and promoting timely consultation with qualified healthcare providers when necessary. By reducing the burden on healthcare facilities and minimizing unnecessary clinical visits, the proposed medical information enquiry chatbot contributes to improved healthcare efficiency and patient empowerment. The combination of machine learning intelligence, conversational computing, accessibility features, and scalable deployment makes the system a valuable addition to modern digital healthcare ecosystems. Overall, this work demonstrates the potential of artificial intelligence–driven chatbots to enhance health awareness, support early-stage medical decision-making, and facilitate informed healthcare engagement in a fast-paced digital environment.
Disclaimer: Curated by HT Syndication.
